Description

Efficient and intelligent music information retrieval MIR performs the task of classiûcation in which it assigns
(MIR) is a need of the 21st century. MIR addresses the problem labels to each song based on genre, mood, artists, etc. Those
of querying and retrieving certain types of music from large tasks directly related to song classiûcation analyzing the
music data set. A singing voice is one of the key elements of singing voice are Singer Identification, Singer Verification,
music. As most part of music is characterized by the performing Music annotation etc. Other extended applications involve
singer, analysis of singing voice reveals many characteristics distinguishing between trained and untrained singer, analyse
of a song. The unique qualities of a singer’s voice make it vocal quality, vocal enhancement etc. The paper provides an
relatively easy for carrying out numerous tasks in MIR. The overview of features and techniques used for the above
singing voice is completely characterized by its acoustic classiûcation tasks. It provides a summary of different
features. Acoustic features like timbre, vibrato, pitch and applications based on singing voice and maps the application
harmony describe the singing voice in the music and these to its best suitable acoustic feature, the extraction method of
are discussed in the paper. There are many applications of that feature and the appropriate classifier. The performance
MIR which considers overall features of music, but the paper parameters that are essential to evaluate the system are also
presents a review of those applications of MIR concerned presented.
directly to singing voice in the music. Also the paper lists the
feature extraction methods and identifies the suitable feature
appropriate for individual task of MIR.

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